Pilot #3: Integration of multiple sources towards personalised preventions
Early diagnosis of dementia is crucial for effective intervention. This study focuses on using biomarkers from cerebrospinal fluid, blood, neuropsychological tests, neuroimaging, and digital speech processing to predict dementia in individuals with MCI. By integrating these data, high-risk individuals can be identified for personalised prevention plans.
Pilot #2: Pattern identification for the development of dementia through analysis of biomarkers
The study aims to collect and identify biomarkers and data related to dementia to predict future cognitive decline in older adults. Non-demented participants concerned about their cognitive status will be recruited. Data collected will include cerebrospinal fluid biomarkers, neuropsychological assessments, medical examinations, MRI, EEG, sleep and activity questionnaires, dietary intake, sleep measures from wearables, and […]
Pilot #1: Integration of lifestyle and genetic factors for assessing the risk of development dementia
The study targets individuals aged 40-60 at risk of cognitive decline or dementia, integrating lifestyle and polygenic risk factors. Participants, recruited from community health programmes, will undergo health assessments and be divided into intervention groups. These groups will receive varying combinations of health coaching and epigenomic feedback, while an observational group will track changes without […]
